Exploring the relationship between medical student basic psychological need satisfaction, resilience, and well-being: a quantitative study
Bibliographic record
Abstract
BACKGROUND: There is increasing acknowledgment that medical training is stressful for students and can impact their well-being. An important aspect of this is self-determination and basic psychological need satisfaction. A better understanding of how medical student perceptions of the learning environment impacts their basic psychological needs for motivation, resilience, and well-being may help to create learning environments that support the needs of medical students and help them become better healthier physicians. We aim to add to the literature on this topic by examining this relationship through the lens of Self-Determination Theory. METHODS: A total of 400 students from all 4 years of the medical program at our institution were invited to complete an anonymous online survey, measuring basic need satisfaction/frustration (autonomy, competence, relatedness) within the learning environment, resilience, and psychological well-being. We used analysis of variance to assess the effect of gender, age, and year on all variables, with t-tests to compare subgroups. Structural equation modelling was performed to test a hypothesized model in which support of medical students' basic needs would positively relate to their resilience and well-being. RESULTS: = 3.15, df = 3, p = 0.369, RMSEA = 0.018, SRMR = 0.022, CFI = 0.999. Autonomy and relatedness satisfaction exerted direct effects on well-being. Competence satisfaction did so indirectly, through its direct effect on resilience. Female medical students had lower resilience scores compared to their male peers. CONCLUSIONS: When medical students perceived their learning environment as supportive to their basic needs, it was associated with an increase in their psychological well-being. Satisfaction of competence, but not autonomy or relatedness, predicted an increase in their resilience. Fostering medical students' basic needs for motivation, especially competence, is recommended to support their resilience and well-being. Further research is required to generalize these results further.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".